Review in detail the set of histograms for the Offline QA Shifts for Fast Offline Data Production (highest priority); the minimum requirement is 1-2 file sequences or 'jobs' per Experiment Run ID number and trigger collection, e.g. st_physics, st_mtd, st_upsilon, minbias, high tower, etc.
Note that for Au-Au one file sequence is usually sufficient however you may need to use the "combine several jobs together" option in order to get enough statistics. Starting this year for Run 11 there are additional options in the QA browser for obtaining and reviewing the QA data. These include: (1) "Combine several jobs together", (2) "New: Select jobs that have been automatically combined", (3) "TESTING: ..." versions of the job selection options which enables automated comparisons with a reference. You may use either option. As the name implies, the "TESTING" option is still under development but you are encouraged to use this feature and provide feed-back to the QA team. This latest automated QA capability will become essential as STAR's DAQ rates continue to increase.
Write a useful and informative Offline QA Shift report using a web-based form noting especially any and all suspected problems with the detectors, calibrations, and reconstruction. The report will be archived and the summary sent to 'starqa-hn' hypernews automatically.
Press the "MARK" button for all fast offline data runs you examined while on shift.
Review the Online Run Log information and comments for each real data production job you examine and summarize the Run/Data Quality status based on the Run Log information and the QA examination results by marking the job as "Good" or "Bad." Jobs will normally be considered "Good" even when there are hardware outages or calibration/reconstruction issues. Please check with the QA experts before marking jobs as "Bad."
Notify the appropriate experts and/or the QA contacts for any and all suspected problems with the detectors, calibrations, or fast-offline reconstruction.
Check the Online-to-Offline data base migration using the "Database Migration Monitor" link on the first page of the QA browser after you login. When data are being taken the first several tables should appear in green font. If no data have been acquired for a day or so then all the tables should be in red. If there are any red fonts in the first several tables labelled "RunLog_onl" while data are being taken then this may indicate a problem and you should notify starqa-hn explicitly.
Summary of Fast Offline QA Shift Duties - Run 12
Review in detail the set of histograms for the Offline QA Shifts for Fast Offline Data Production (highest priority); the minimum requirement is 1-2 file sequences or 'jobs' per Experiment Run ID number and trigger collection, e.g. st_physics, st_mtd, st_upsilon, minbias, high tower, etc.
Note that for p-p the "combine several jobs together" option is recommended in order to get enough statistics. For Au-Au one file sequence is usually adequate but the combined jobs option is still recommended. Npte that there are additional options in the QA browser for obtaining and reviewing the QA data. These include: (1) "Combine several jobs together", (2) "New: Select jobs that have been automatically combined", (3) "TESTING: ..." versions of the job selection options which enables automated comparisons with a reference. You may use either option. As the name implies, the "TESTING" option, which was introduced in Run 11, may continue to see some further development upgrades this year, but you are encouraged to use this feature and provide feed-back to the QA team. This latest automated QA capability will become essential as STAR's DAQ rates continue to increase.
Write a useful and informative Offline QA Shift report using a web-based form noting especially any and all suspected problems with the detectors, calibrations, and reconstruction. The report will be archived and the summary sent to 'starqa-hn' hypernews automatically.
Press the "MARK" button for all fast offline data runs you examined while on shift.
Review the Online Run Log information and comments for each real data production job you examine and summarize the Run/Data Quality status based on the Run Log information and the QA examination results by marking the job as "Good" or "Bad." Jobs will normally be considered "Good" even when there are hardware outages or calibration/reconstruction issues. Please check with the QA experts before marking jobs as "Bad."
Notify the appropriate experts and/or the QA contacts for any and all suspected problems with the detectors, calibrations, or fast-offline reconstruction.
Check the Online-to-Offline data base migration using the "Database Migration Monitor" link on the first page of the QA browser after you login. When data are being taken the first several tables should appear in green font. If no data have been acquired for a day or so then all the tables should be in red. If there are any red fonts in the first several tables labelled "RunLog_onl" while data are being taken then this may indicate a problem and you should notify starqa-hn explicitly.
Using the Automated QA browser review in detail the set of histograms for the Offline QA Shifts for Fast Offline Data Production (highest priority); the minimum requirement is 1-2 file sequences or 'jobs' per Experiment Run ID number and trigger collection, e.g. st_physics, st_mtd, st_upsilon, minbias, high tower, etc.
Note that for p-p the "Auto-combined" or the "combine several jobs" option is recommended in order to get enough statistics. For Au-Au one file sequence is usually adequate but either combine jobs option is still recommended. Note that starting this year the presentation of the QA histograms and references have changed. The "testing" options introduced last year are now to be used routinely.
Write a useful and informative Offline QA Shift report using a web-based form noting especially any and all suspected problems with the detectors, calibrations, and reconstruction. The report will be archived and the summary sent to 'starqa-hn' hypernews automatically. Please use the "play" mode if you are a first-time user to practice filling out the report.
Review the Online Run Log information and comments for each real data production job you examine and summarize the Run/Data Quality status based on the Run Log information and the QA examination results by marking the job as "Good" or "Bad." This will also indicate that the data have been examined by Offline QA. Jobs will normally be considered "Good" even when there are hardware outages or calibration/reconstruction issues. Please check with the QA experts before marking jobs as "Bad."
Notify the appropriate experts and/or the QA contacts for any and all suspected problems with the detectors, calibrations, or fast-offline reconstruction.
Check the Online-to-Offline data base migration using the "Database Migration Monitor" link on the first page of the QA browser after you login. When data are being taken the first several tables should appear in green font. If no data have been acquired for a day or so then all the tables should be in red. If there are any red fonts in the first several tables labelled "RunLog_onl" while data are being taken then this may indicate a problem and you should notify starqa-hn explicitly.